如果条件满足，则在 dataframe 中打开 NaN

Question

我这里有一列看起来像这样，是 dataframe 的一部分：

df.Days_Since_Earnings
Out[5]: 
0      21.0
2       1.0
4    1000.0
5     500.0
6     119.0
Name: Days_Since_Earnings, Length: 76, dtype: float64

我想保持原样，除了我想把 120 以上的数字变成 'nan's，所以它看起来像这样：

df.Days_Since_Earnings
Out[5]: 
0      21.0
2       1.0
4       nan
5       nan
6     119.0
Name: Days_Since_Earnings, Length: 76, dtype: float64

感谢任何帮助的人！

Answer 1

您可以使用mask ：

df['Days_Since_Earnings'] = df.Days_Since_Earnings.mask(df.Days_Since_Earnings > 120)

或where相反条件的地方

df['Days_Since_Earnings'] = df.Days_Since_Earnings.where(df.Days_Since_Earnings <= 120)

或loc分配：

df.loc[df.Days_Since_Earnings > 120, 'Days_Since_Earnings'] = np.nan

Answer 2

df['days'] = df['days'].apply(lambda x: np.nan if x > 120 else x)
print(df)

或者

df[df['days'] > 120] = np.nan

    days
0   21.0
1    1.0
2    NaN
3    NaN
4  119.0